On completion of the programme students should be able to demonstrate:
- A systematic understanding of the theory and practice of designing and implementing Cloud systems;
- Proficiency in the technical and programming skills required to design and implement Cloud systems;
- A thorough knowledge and skills base in a number of advanced topics within the domain of distributed computer systems including Grids and Clouds;
- An in-depth knowledge of the essential principles and practices used in the effective design, implementation and usability of Cloud systems including virtualization, scalability, performance, security, and dependability;
- The ability to apply these principles and practices to tackle a significant problem within the main project;
- An in-depth understanding of an area of specialisation, gained during the main project;
- Be confident in applying the research methodology adopted for the main project on new problems;
- Be prepared for further study either in the context of professional development or through further engagement in higher education.
The programme will:
- Situate the study of Cloud systems within the general context of computational modelling and complex systems;
- Give a broad perspective on Cloud systems, covering service-oriented design models, service-oriented architecture (SOA), service-level agreement (SLA), algorithms and mechanisms for dynamic service integration, security and dependability, virtualisation, scalability, and energy efficiency.
- Be rooted in established research strengths of the School and will offer the opportunity for students to work as integral members of our research groups during their main project;
- Prepare graduates for graduate careers in the IT industry and other contexts or for further study either in the context of continuing professional development or through further engagement in higher education.
[Learning Outcomes, Transferable (Key) Skills, Assessment]
View Timetable
Candidates will be required to study the following compulsory modules:
Code | Title | Credits | Semester | Pass for Progression |
---|---|---|---|---|
COMP5123M | Cloud Computing Systems | 15 | Semester 2 (Jan to Jun) | |
COMP5200M | MSc Project | 60 | 1 Jan to 30 Sep | PFP |
COMP5911M | Advanced Software Engineering | 15 | Semester 1 (Sep to Jan) |
Candidates will be required to study 90 credits from the following lists of optional modules:
Code | Title | Credits | Semester | Pass for Progression |
---|---|---|---|---|
COMP5122M | Data Science | 15 | Semester 1 (Sep to Jan) | |
COMP5125M | Blockchain Technologies | 15 | Semester 2 (Jan to Jun) | |
COMP5450M | Knowledge Representation and Reasoning | 15 | Semester 1 (Sep to Jan) | |
COMP5611M | Machine Learning | 15 | Semester 2 (Jan to Jun) | |
COMP5625M | Deep Learning | 15 | Semester 2 (Jan to Jun) | |
COMP5710M | Algorithms | 15 | Semester 1 (Sep to Jan) | |
COMP5712M | Programming for Data Science | 15 | Semester 1 (Sep to Jan) | |
COMP5840M | Data Mining and Text Analytics | 15 | Semester 2 (Jan to Jun) | |
COMP5930M | Scientific Computation | 15 | Semester 1 (Sep to Jan) |
Last updated: 05/12/2024 09:23:39
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